scholarly journals Response of the Wintertime Northern Hemisphere Atmospheric Circulation to Current and Projected Arctic Sea Ice Decline: A Numerical Study with CAM5

2014 ◽  
Vol 27 (1) ◽  
pp. 244-264 ◽  
Author(s):  
Yannick Peings ◽  
Gudrun Magnusdottir

Abstract The wintertime Northern Hemisphere (NH) atmospheric circulation response to current (2007–12) and projected (2080–99) Arctic sea ice decline is examined with the latest version of the Community Atmospheric Model (CAM5). The numerical experiments suggest that the current sea ice conditions force a remote atmospheric response in late winter that favors cold land surface temperatures over midlatitudes, as has been observed in recent years. Anomalous Rossby waves forced by the sea ice anomalies penetrate into the stratosphere in February and weaken the stratospheric polar vortex, resulting in negative anomalies of the northern annular mode (NAM) that propagate downward during the following weeks, especially over the North Pacific. The seasonality of the response is attributed to timing of the phasing between the forced and climatological waves. When sea ice concentration taken from projections of conditions at the end of the twenty-first century is prescribed to the model, negative anomalies of the NAM are visible in the troposphere, both in early and late winter. This response is mainly driven by the large warming of the lower troposphere over the Arctic, as little impact is found in the stratosphere in this experiment. As a result of the thermal expansion of the polar troposphere, the westerly flow is decelerated and a weak but statistically significant increase of the midlatitude meanders is identified. However, the thermodynamical response extends beyond the Arctic and offsets the dynamical effect, such that the stronger sea ice forcing has limited impact on the intensity of cold extremes over midlatitudes.

2016 ◽  
Vol 29 (14) ◽  
pp. 5103-5122 ◽  
Author(s):  
Xiao-Yi Yang ◽  
Xiaojun Yuan ◽  
Mingfang Ting

Abstract The recent accelerated Arctic sea ice decline has been proposed as a possible forcing factor for midlatitude circulation changes, which can be projected onto the Arctic Oscillation (AO) and/or North Atlantic Oscillation (NAO) mode. However, the timing and physical mechanisms linking AO responses to the Arctic sea ice forcing are not entirely understood. In this study, the authors suggest a connection between November sea ice extent in the Barents and Kara Seas and the following winter’s atmospheric circulation in terms of the fast sea ice retreat and the subsequent modification of local air–sea heat fluxes. In particular, the dynamical processes that link November sea ice in the Barents and Kara Seas with the development of AO anomalies in February is explored. In response to the lower-tropospheric warming associated with the initial thermal effect of the sea ice loss, the large-scale atmospheric circulation goes through a series of dynamical adjustment processes: The decelerated zonal-mean zonal wind anomalies propagate gradually from the subarctic to midlatitudes in about one month. The equivalent barotropic AO dipole pattern develops in January because of wave–mean flow interaction and firmly establishes itself in February following the weakening and warming of the stratospheric polar vortex. This connection between sea ice loss and the AO mode is robust on time scales ranging from interannual to decadal. Therefore, the recent winter AO weakening and the corresponding midlatitude climate change may be partly associated with the early winter sea ice loss in the Barents and Kara Seas.


2014 ◽  
Vol 14 (7) ◽  
pp. 10929-10999 ◽  
Author(s):  
R. Döscher ◽  
T. Vihma ◽  
E. Maksimovich

Abstract. The Arctic sea ice is the central and essential component of the Arctic climate system. The depletion and areal decline of the Arctic sea ice cover, observed since the 1970's, have accelerated after the millennium shift. While a relationship to global warming is evident and is underpinned statistically, the mechanisms connected to the sea ice reduction are to be explored in detail. Sea ice erodes both from the top and from the bottom. Atmosphere, sea ice and ocean processes interact in non-linear ways on various scales. Feedback mechanisms lead to an Arctic amplification of the global warming system. The amplification is both supported by the ice depletion and is at the same time accelerating the ice reduction. Knowledge of the mechanisms connected to the sea ice decline has grown during the 1990's and has deepened when the acceleration became clear in the early 2000's. Record summer sea ice extents in 2002, 2005, 2007 and 2012 provided additional information on the mechanisms. This article reviews recent progress in understanding of the sea ice decline. Processes are revisited from an atmospheric, ocean and sea ice perspective. There is strong evidence for decisive atmospheric changes being the major driver of sea ice change. Feedbacks due to reduced ice concentration, surface albedo and thickness allow for additional local atmosphere and ocean influences and self-supporting feedbacks. Large scale ocean influences on the Arctic Ocean hydrology and circulation are highly evident. Northward heat fluxes in the ocean are clearly impacting the ice margins, especially in the Atlantic sector of the Arctic. Only little indication exists for a direct decisive influence of the warming ocean on the overall sea ice cover, due to an isolating layer of cold and fresh water underneath the sea ice.


2020 ◽  
Vol 47 (3) ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Xuezhu Wang ◽  
Sergey Danilov ◽  
Nikolay Koldunov ◽  
...  

2016 ◽  
Vol 29 (2) ◽  
pp. 889-902 ◽  
Author(s):  
Rasmus A. Pedersen ◽  
Ivana Cvijanovic ◽  
Peter L. Langen ◽  
Bo M. Vinther

Abstract Reduction of the Arctic sea ice cover can affect the atmospheric circulation and thus impact the climate beyond the Arctic. The atmospheric response may, however, vary with the geographical location of sea ice loss. The atmospheric sensitivity to the location of sea ice loss is studied using a general circulation model in a configuration that allows combination of a prescribed sea ice cover and an active mixed layer ocean. This hybrid setup makes it possible to simulate the isolated impact of sea ice loss and provides a more complete response compared to experiments with fixed sea surface temperatures. Three investigated sea ice scenarios with ice loss in different regions all exhibit substantial near-surface warming, which peaks over the area of ice loss. The maximum warming is found during winter, delayed compared to the maximum sea ice reduction. The wintertime response of the midlatitude atmospheric circulation shows a nonuniform sensitivity to the location of sea ice reduction. While all three scenarios exhibit decreased zonal winds related to high-latitude geopotential height increases, the magnitudes and locations of the anomalies vary between the simulations. Investigation of the North Atlantic Oscillation reveals a high sensitivity to the location of the ice loss. The northern center of action exhibits clear shifts in response to the different sea ice reductions. Sea ice loss in the Atlantic and Pacific sectors of the Arctic cause westward and eastward shifts, respectively.


2015 ◽  
Vol 112 (15) ◽  
pp. 4570-4575 ◽  
Author(s):  
Rong Zhang

Satellite observations reveal a substantial decline in September Arctic sea ice extent since 1979, which has played a leading role in the observed recent Arctic surface warming and has often been attributed, in large part, to the increase in greenhouse gases. However, the most rapid decline occurred during the recent global warming hiatus period. Previous studies are often focused on a single mechanism for changes and variations of summer Arctic sea ice extent, and many are based on short observational records. The key players for summer Arctic sea ice extent variability at multidecadal/centennial time scales and their contributions to the observed summer Arctic sea ice decline are not well understood. Here a multiple regression model is developed for the first time, to the author’s knowledge, to provide a framework to quantify the contributions of three key predictors (Atlantic/Pacific heat transport into the Arctic, and Arctic Dipole) to the internal low-frequency variability of Summer Arctic sea ice extent, using a 3,600-y-long control climate model simulation. The results suggest that changes in these key predictors could have contributed substantially to the observed summer Arctic sea ice decline. If the ocean heat transport into the Arctic were to weaken in the near future due to internal variability, there might be a hiatus in the decline of September Arctic sea ice. The modeling results also suggest that at multidecadal/centennial time scales, variations in the atmosphere heat transport across the Arctic Circle are forced by anticorrelated variations in the Atlantic heat transport into the Arctic.


2020 ◽  
Vol 47 (1) ◽  
Author(s):  
Yu‐Chiao Liang ◽  
Young‐Oh Kwon ◽  
Claude Frankignoul ◽  
Gokhan Danabasoglu ◽  
Stephen Yeager ◽  
...  

2019 ◽  
Vol 32 (15) ◽  
pp. 4731-4752 ◽  
Author(s):  
Axel J. Schweiger ◽  
Kevin R. Wood ◽  
Jinlun Zhang

Abstract PIOMAS-20C, an Arctic sea ice reconstruction for 1901–2010, is produced by forcing the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) with ERA-20C atmospheric data. ERA-20C performance over Arctic sea ice is assessed by comparisons with measurements and data from other reanalyses. ERA-20C performs similarly with respect to the annual cycle of downwelling radiation, air temperature, and wind speed compared to reanalyses with more extensive data assimilation such as ERA-Interim and MERRA. PIOMAS-20C sea ice thickness and volume are then compared with in situ and aircraft remote sensing observations for the period of ~1950–2010. Error statistics are similar to those for PIOMAS. We compare the magnitude and patterns of sea ice variability between the first half of the twentieth century (1901–40) and the more recent period (1980–2010), both marked by sea ice decline in the Arctic. The first period contains the so-called early-twentieth-century warming (ETCW; ~1920–40) during which the Atlantic sector saw a significant decline in sea ice volume, but the Pacific sector did not. The sea ice decline over the 1979–2010 period is pan-Arctic and 6 times larger than the net decline during the 1901–40 period. Sea ice volume trends reconstructed solely from surface temperature anomalies are smaller than PIOMAS-20C, suggesting that mechanisms other than warming, such as changes in ice motion and deformation, played a significant role in determining sea ice volume trends during both periods.


2014 ◽  
Vol 27 (2) ◽  
pp. 527-550 ◽  
Author(s):  
Justin J. Wettstein ◽  
Clara Deser

Abstract Internal variability in twenty-first-century summer Arctic sea ice loss and its relationship to the large-scale atmospheric circulation is investigated in a 39-member Community Climate System Model, version 3 (CCSM3) ensemble for the period 2000–61. Each member is subject to an identical greenhouse gas emissions scenario and differs only in the atmospheric model component's initial condition. September Arctic sea ice extent trends during 2020–59 range from −2.0 × 106 to −5.7 × 106 km2 across the 39 ensemble members, indicating a substantial role for internal variability in future Arctic sea ice loss projections. A similar nearly threefold range (from −7.0 × 103 to −19 × 103 km3) is found for summer sea ice volume trends. Higher rates of summer Arctic sea ice loss in CCSM3 are associated with enhanced transpolar drift and Fram Strait ice export driven by surface wind and sea level pressure patterns. Over the Arctic, the covarying atmospheric circulation patterns resemble the so-called Arctic dipole, with maximum amplitude between April and July. Outside the Arctic, an atmospheric Rossby wave train over the Pacific sector is associated with internal ice loss variability. Interannual covariability patterns between sea ice and atmospheric circulation are similar to those based on trends, suggesting that similar processes govern internal variability over a broad range of time scales. Interannual patterns of CCSM3 ice–atmosphere covariability compare well with those in nature and in the newer CCSM4 version of the model, lending confidence to the results. Atmospheric teleconnection patterns in CCSM3 suggest that the tropical Pacific modulates Arctic sea ice variability via the aforementioned Rossby wave train. Large ensembles with other coupled models are needed to corroborate these CCSM3-based findings.


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